Mobile communication devices are in use throughout everyday life. One common aspect to the use of mobile communication devices is that they are often used in noisy environments. In particular, mobile communication devices are often used in vehicle cabins, such as cars, trains, airplanes, and the like, which tend to have a considerable amount of low level background noise.
As such, there has been a lot of money and effort devoted to developing systems and methods for reducing noise in communication signals that are generated in a noisy environment. These systems and methods have ranged from very simple filtering to very complex digital signal processing algorithms. The more complex algorithms often involve breaking a signal into various frames and performing various computations on each of the frames to try to remove noise from each frame, and thus, from the signal. Unfortunately, the more simple methods typically do not remove enough noise or cause the voice signal to be less intelligible while the more complex methods are typically more computationally intensive and require greater processing power and processing time to produce the adjusted signal, often with unpredictable effects on the removal of noise from the signal.
There remains a need for an efficient and relatively simple (i.e. less computationally intensive) system and method for reducing uplink noise on a communication signal.